Image Enhancement and Change Detection

This unit develops practical skills in advanced remote sensing image enhancement, spectral transformations, and multi-temporal change detection, integrating SAR coherence, stereo-derived 3D data, and neighborhood operations. Students will also learn GIS data structures, coordinate system selection, metadata/standards, and raster–vector map algebra to prepare and integrate processed imagery for applied analyses such as land‑use change and geohazard assessment.

Learning Objectives

• Analyze and compare image enhancement techniques (histogram equalization/matching, Gaussian stretch, de‑correlation stretch, local contrast, high‑pass filters) to select appropriate methods for specific remote sensing tasks
• Apply spectral index derivation, band math, RGB⇄IHS and tasseled‑cap transformations to extract surface parameters and improve feature discrimination for landcover and vegetation analysis
• Demonstrate multi‑temporal SAR coherence, spatial de‑correlation, ratio coherence, and very narrow‑baseline stereo matching workflows to detect and quantify change, ground motion, and generate 3D surface data
• Evaluate GIS data structures, select suitable coordinate systems, and implement metadata/interoperability standards while performing neighborhood operations and raster–vector map algebra to integrate results for risk and hazard weighting